Dataset Iris (targetcl. Iris-setosa)

Basic characteristics Iris (targetcl. Iris-setosa)

50

target objects

Iris Plant database from UCI. A classic dataset in the pattern recognition literature. The original dataset is a multiclass classification problem, introduced by R.A. Fisher, The use of multiple measurements in taxonomic problems. Ann Eugenics, 7:179--188, 1936. Download mat-file with Prtools dataset.

100

outlier objects

4

features

Unsupervised PCA Iris (targetcl. Iris-setosa)

On the left, the PCA scatterplot is shown, on the right
the retained variance for varying number of features.

On the left, the PCA scatterplot is shown of data
rescaled to unit variance, on the right the
retained variance.

Supervised Fisher Iris (targetcl. Iris-setosa)

On the left, the Fisher scatterplot is shown, on the
right the ROC curve along this direction.

Classifier projection spaces The first classifier projection spaces are obtained by computing the classifier label disagreements (setting the threshold on 10% target error) and applying an MDS on the resulting distance matrix between classifiers:

Original

Unit variance

PCA mapped

Classifier projection spaces The second versions of the classifier projection spaces are obtained by computing the classifier ranking disagreements and applying an MDS on the resulting distance matrix between classifiers: